Compositional space parameterization methods for thermal-compositional simulation

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Abstract/Contents

Abstract
Compositional simulation is necessary for the modeling of complex Enhanced Oil Recovery processes (EOR), such as gas and steam injection. Accurate simulation of these EOR processes involves coupling the nonlinear conservation laws for multicomponent, multiphase flow and transport with the equations that describes the phase behavior of the mixture at thermodynamic equilibrium. Phase-behavior modeling requires extensive computations and consumes significant time. The computational cost associated with the phase-behavior calculations increases significantly for systems where three or more fluid phases coexist at equilibrium. We present a family of methods for the computation of the thermodynamic phase-behavior associated with multicomponent, multiphase flow in porous media. These methods are based on concepts developed in the analytical theory of one-dimensional gas-injection processes. For two-phase compositional simulation, we present a Compositional Space Parameterization (CSP) framework, in which the thermodynamic phase-behavior is reformulated in the tie-simplex space as a function of composition, pressure, and phase fractions. This tie-simplex space is then used to specify the base nonlinear variables for fully-implicit compositional simulation. The tie-simplex space is discretized, and multilinear interpolation of the thermodynamic relations is employed. Thus, all the thermodynamic properties become piece-wise linear functions in the tie-simplex space. The computation of the phase behavior in the course of a compositional simulation then becomes an iteration-free procedure and does not require any Equation of State (EoS) computations (flash computations or phase-stability tests). We demonstrate that the proposed CSP method reduces the computational cost of the thermodynamic calculations significantly compared with standard EoS-based approaches. Moreover, the proposed framework is promising not only for acceleration of phase-behavior computations, but more importantly as a new thermodynamically consistent approximation for general-purpose compositional simulation. Next, for the general case of multiphase (three, and more phases) simulation, we study the importance of using EoS-based modeling for thermal reservoir simulation. Here, the EoS-based approach is compared with the industry standard K-values method. The analysis employs simple one-dimensional thermal displacements of heavy oil by a mixture of steam and solvent. This analysis shows that three-phase EoS-based computations may be necessary for accurate modeling of certain types of thermal EOR processes. Finally, we develop an extension of the CSP framework for multicomponent, multiphase thermal-compositional simulation. In particular, we present a strategy for phase-state identification that can be used to bypass the need for full three-phase EoS computations. The method uses information from the parameterized extensions of the `key' tie-simplexes and is based on the adaptive discretization of the extensions of these tie-simplexes. We demonstrate the efficiency and robustness of the developed bypass strategy for the simulation of flow and transport in thermal, three-phase compositional models of heterogeneous reservoirs.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Copyright date 2015
Publication date 2014, 2015; 2014
Issuance monographic
Language English

Creators/Contributors

Associated with Zaydullin, Rustem
Associated with Stanford University, Department of Energy Resources Engineering.
Primary advisor Tchelepi, Hamdi
Thesis advisor Tchelepi, Hamdi
Thesis advisor Kovscek, Anthony R. (Anthony Robert)
Thesis advisor Voskov, Denis
Advisor Kovscek, Anthony R. (Anthony Robert)
Advisor Voskov, Denis

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Rustem Zaydullin.
Note Submitted to the Department of Energy Resources Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2015.
Location electronic resource

Access conditions

Copyright
© 2015 by Rustem Zaydullin
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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